22 citations · 22 across the 5 of their papers we have counts for
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One-Step Diffusion with Inverse Residual Fields for Unsupervised Industrial Anomaly Detection
Boan Zhang, Wen Li, Guanhua Yu +3
Diffusion models have achieved outstanding performance in unsupervised industrial anomaly detection (uIAD) by learning a manifold of normal data under the common assumption that of…
FastRef:Fast Prototype Refinement for Few-Shot Industrial Anomaly Detection
Long Tian, Yufei Li, Yuyang Dai +3
Few-shot industrial anomaly detection (FS-IAD) presents a critical challenge for practical automated inspection systems operating in data-scarce environments. While existing approa…
Low-Rank Adaptation of Pre-Trained Stable Diffusion for Rigid-Body Target ISAR Imaging
Boan Zhang, Hang Dong, Jiongge Zhang +5
Traditional range-instantaneous Doppler (RID) methods for rigid-body target imaging often suffer from low resolution due to the limitations of time-frequency analysis (TFA). To add…
WikiStyle+: A Multimodal Approach to Content-Style Representation Disentanglement for Artistic Image Stylization
Ma Zhuoqi, Zhang Yixuan, You Zejun +2
Artistic image stylization aims to render the content provided by text or image with the target style, where content and style decoupling is the key to achieve satisfactory results…
Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection
Ruiying Lu, YuJie Wu, Long Tian +4
Unsupervised image Anomaly Detection (UAD) aims to learn robust and discriminative representations of normal samples. While separate solutions per class endow expensive computation…